Literature DB >> 18458805

Mathematical modelling of Mycobacterium tuberculosis VNTR loci estimates a very slow mutation rate for the repeats.

Andrew Grant1, Catherine Arnold, Nicola Thorne, Saheer Gharbia, Anthony Underwood.   

Abstract

Minisatellites are highly variable tandem repeats used for over 20 years in humans for DNA fingerprinting. In prokaryotes fingerprinting techniques exploiting VNTR (variable number of tandem repeats) polymorphisms have become widely used recently in bacterial typing. However although many investigations into the mechanisms underlying minisatellite variation in humans have been performed, relatively little is known about the processes that mediate bacterial minisatellite polymorphism. An understanding of this is important since it will influence how the results from VNTR experiments are interpreted. The minisatellites of Mycobacterium tuberculosis are well characterized since they are some of the few polymorphic loci in what is otherwise a very homogeneous organism. Using VNTR results from a well-defined and characterized set of M. tuberculosis strains we show that the repeats at a locus are likely to evolve by stepwise contraction or expansion in the number of repeats. A stochastic continuous-time population mathematical model was developed to simulate the evolution of the repeats. This allowed estimation of the tendency of the repeats to increase or decrease and the rate at which they change. The majority of loci tend to lose rather than gain repeats. All of the loci mutate extremely slowly, with an average rate of 2.3 x 10(-8), which is 350 times slower than that of a set of VNTR repeats with similar diversity observed experimentally in Escherichia coli. This suggests that the VNTR profile of a strain of M. tuberculosis will be indicative of its clonal lineage and will be unlikely to vary in epidemiologically-related strains.

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Year:  2008        PMID: 18458805     DOI: 10.1007/s00239-008-9104-6

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  31 in total

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Journal:  Emerg Infect Dis       Date:  2002-11       Impact factor: 6.883

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Authors:  Philip Supply; Robin M Warren; Anne-Laure Bañuls; Sarah Lesjean; Gian D Van Der Spuy; Lee-Anne Lewis; Michel Tibayrenc; Paul D Van Helden; Camille Locht
Journal:  Mol Microbiol       Date:  2003-01       Impact factor: 3.501

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  10 in total

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